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# Googleドライブをマウント
from google.colab import drive
drive.mount('/content/gdrive')
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# Open3Dをインストール
!pip install open3d
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
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# Open3Dのバージョン確認 (Ver 0.16.0以上であるのを確認します)
import open3d as o3d
o3d.__version__
'0.16.0'
[ ]:
# Open3DとNumpy などをインポートします
import os
import open3d as o3d
import numpy as np
import copy
[ ]:
# 3次元モデル読み込み
file_path = "/content/gdrive/MyDrive/dataset/image_in/fire_hydrant.ply" # ファイルパスを設定
fp_mesh = o3d.io.read_triangle_mesh(file_path) # メッシュデータ読み込み
o3d.visualization.draw_plotly([fp_mesh]) # メッシュデータ表示
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# 法線ベクトルを計算
fp_mesh.compute_vertex_normals() # 法線計算
o3d.visualization.draw_plotly([fp_mesh], mesh_show_wireframe=True) # メッシュをフレーム付きで表示
[ ]:
# メッシュポリゴンから点群への変換
fp_point = fp_mesh.sample_points_uniformly(number_of_points=10000) # メッシュからポイントデータ作成
o3d.visualization.draw_plotly([fp_point]) # ポイントデータ表示
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# 点数のポイントを減らす
fp_point_down = fp_point.voxel_down_sample(voxel_size=0.001) # ポイントデータを間引き
o3d.visualization.draw_plotly([fp_point_down], width=640, height=400) # 間引きしたポイントデータを表示. 表示サイズを指定
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# 移動：並進移動
def translate(mesh):
mesh_t = copy.deepcopy(mesh).translate([10, 10, 10]) # データをコピーして、X,Y,Zの移動量を設定
o3d.visualization.draw_plotly([mesh, mesh_t]) # 元データと移動したデータを並べて表示
translate(fp_mesh) # メッシュデータを移動表示
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# 回転：軸角度からデータを回転
# メッシュデータを表示
def rotate_axis(mesh):
mesh_r = copy.deepcopy(mesh).translate((10, 0, 0)) # 並べ表示用するために、移動量を指定してコピー
rotation_matrix = o3d.geometry.get_rotation_matrix_from_axis_angle([np.radians(90), 0, 0]) # 回転行列に変換
mesh_r.rotate(rotation_matrix) # データ回転
o3d.visualization.draw_plotly([mesh, mesh_r]) # 元データと回転したデータを表示
rotate_axis(fp_mesh) # メッシュデータを回転表示
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# 回転：オイラー角を使用してデータを回転
# ポイントデータを表示
def rotate_xyz(mesh):
mesh_r = copy.deepcopy(mesh).translate((10, 0, 0)) # 並べ表示用するために、移動量を指定してコピー
rotation_matrix = o3d.geometry.get_rotation_matrix_from_xyz((0, np.pi / 2, 0)) # 回転行列に変換
mesh_r.rotate(rotation_matrix) # 回転
mesh.paint_uniform_color([0.5, 0.0, 0.0]) # 元データを赤表示
mesh_r.paint_uniform_color([0.0, 0.5, 0.0]) # 回転データを緑表示
o3d.visualization.draw_plotly([mesh, mesh_r]) # 元データと回転したデータを表示
rotate_xyz(fp_point) # ポイントデータを回転表示
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# スケール： データを拡大・縮小
def scale(mesh):
mesh_s = copy.deepcopy(mesh).translate((10, 0, 0)) # 並べ表示用するために、移動量を指定してコピー
mesh_s.scale(0.5, center=mesh_s.get_center()) # メッシュデータの中心を軸に、スケールデータ作成
o3d.visualization.draw_plotly([mesh, mesh_s]) # 元データとスケールしたデータを表示
scale(fp_mesh) # メッシュデータをスケール表示
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# 転換［変換]： 同次変換行列して、回転と並進移動
def transform(mesh):
T = np.eye(4) # 単位行列
T[:3, :3] = o3d.geometry.get_rotation_matrix_from_xyz((np.pi, 0, 0)) # 回転行列
T[0, 3] = 10 # Xの移動量
T[1, 3] = 5 # Yの移動量
print(T) # 変換行列を表示
mesh_t = copy.deepcopy(mesh).transform(T) # 回転と並進移動したデータをコピー
o3d.visualization.draw_plotly([mesh, mesh_t]) # 元データと変換したデータを表示
transform(fp_mesh) # メッシュデータを変換表示
[[ 1.0000000e+00 0.0000000e+00 0.0000000e+00 1.0000000e+01]
[ 0.0000000e+00 -1.0000000e+00 -1.2246468e-16 5.0000000e+00]
[ 0.0000000e+00 1.2246468e-16 -1.0000000e+00 0.0000000e+00]
[ 0.0000000e+00 0.0000000e+00 0.0000000e+00 1.0000000e+00]]